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Found 5 papers, 0 papers with code
Ensemble Reinforcement Learning: A Survey
By offering guidance for future scientific research and engineering applications, this survey significantly contributes to the advancement of ERL.
An Overview and Experimental Study of Learning-based Optimization Algorithms for Vehicle Routing Problem
Vehicle routing problem (VRP) is a typical discrete combinatorial optimization problem, and many models and algorithms have been proposed to solve the VRP and its variants.
A Two-stage Framework and Reinforcement Learning-based Optimization Algorithms for Complex Scheduling Problems
This offers a novel and general paradigm that combines RL with OR approaches to solving scheduling problems, which leverages the respective strengths of RL and OR: The MDP narrows down the search space of the original problem through an RL method, while the mixed-integer programming process is settled by an OR algorithm.
One-sample Guided Object Representation Disassembling
In this paper, we introduce the One-sample Guided Object Representation Disassembling (One-GORD) method, which only requires one annotated sample for each object category to learn disassembled object representation from unannotated images.
Disassembling Object Representations without Labels
In this paper, we study a new representation-learning task, which we termed as disassembling object representations.
